Definition · data warehousing
Data lake
Data lake is a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying structure only when queried. For data lake, a useful definition states a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying, who owns it, and which decision it supports.
Also known as enterprise data lake
Why it matters
Understanding data lake matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. When the term is tied to a source system, owner, and review cadence, it becomes easier to audit assumptions, catch changes early, and keep operators aligned.
In practice
Operating example
Data lake is useful when teams need a shared interpretation of a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying structure only when queried. The definition should make source data, timing, ownership, and the decision it supports explicit.
Review example
Data lake should be reviewed whenever the source system, calculation logic, time period, or decision owner changes. That keeps the definition useful instead of letting it drift into a label.
In practice, teams should define data lake with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding data lake matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. When the term is tied to a source system, owner, and review cadence, it becomes easier to audit assumptions, catch changes early, and keep operators aligned.
A strong workflow for data lake separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
FAQ
What is a data lake?
Data lake is a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying structure only when queried. For data lake, a useful definition states a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying, who owns it, and which decision it supports.
What is the difference between a data lake and a data warehouse?
The boundary for data lake differs from related terms by scope, source data, time period, and decision use. In this glossary, it covers a centralized repository that stores raw structured and unstructured data at any scale on a schema-on-read basis, applying structure only when queried, so teams should compare those boundaries before using it in reporting or planning.